Living Document — Definitions, metadata, and structural references are continuously refined within the Refinement Window (§31, V6 Disclaimer). The current version is the canonical state; previous versions remain accessible via git history and via the immutable Zenodo DOI versions.
Lebendiges Dokument — Definitionen, Metadaten und strukturelle Referenzen werden kontinuierlich innerhalb des Refinement-Windows verfeinert (§31, V6 Disclaimer). Frühere Versionen via git-Historie und über die unveränderlichen Zenodo-DOI-Versionen.
Universal Performance Factor Analysis Framework for Intelligent Entities, Business Teams, and World-Class Performers
Live: https://andreasehstandlicenseofclarityloc.github.io/permanitai-framework/
PERMANITAI transfers the mature, validated methodology of Leistungsfaktorenanalyse (Performance Factor Analysis) from sports science to a universal framework applicable to any entity whose performance depends on interacting factors.
The framework decomposes performance into 5 interdependent factors across 12 application domains:
| Factor | Code | Sports Origin | Universal Transfer |
|---|---|---|---|
| Physical/Hardware | PF-PHY | Strength, endurance, speed | Compute, budget, energy, infrastructure |
| Technical | PF-TEC | Stroke technique, movement quality | Execution quality, tool competence, method mastery |
| Tactical | PF-TAK | Match strategy, opponent analysis | Strategy, planning, resource allocation |
| Psychological/Alignment | PF-PSY | Motivation, pressure handling | Alignment, resilience, trust calibration |
| Contextual | PF-KON | Surface, weather, audience | Environment, regulation, market, culture |
- DOM-USR — Human AI User
- DOM-AIM — AI Model
- DOM-AGT — Single Agent
- DOM-AGT-TEAM — Agent Team
- DOM-ROB — Robot
- DOM-DRN — Drone
- DOM-MRB — Micro-Robot
- DOM-ROB-TEAM — Robot Team
- DOM-HYB — Hybrid System (any combination)
- DOM-BIZ — Business Team / Organization
- DOM-ELITE — World-Class Performer (CEOs, surgeons, scientists, athletes)
- DOM-MGR — Manager / Leader
Current AI evaluation uses siloed benchmarks per entity type. PERMANITAI proposes a unified diagnostic protocol:
- Observe performance
- Decompose into the 5 factors
- Measure each factor independently
- Identify the bottleneck factor
- Design targeted intervention
- Re-measure to verify improvement
This protocol is substrate-independent — it works for a tennis player, an AI agent, a business team, or a surgical team.
PERMANITAI doesn't transfer entities ("a drone is like a striker") — it transfers the diagnostic protocol of sports science:
- MT-001: Diagnostic Protocol — identical analysis logic across entity boundaries
- MT-002: Factor Interaction Analysis — what benchmarks cannot capture
- MT-003: Degradation Profiling — how performance degrades under load
- MT-004: Periodization — training/optimization cycles as universal structure
- MT-005: Team Tactical Analysis — team performance ≠ sum of individual performances
- MT-006: Competition vs. Training Analysis — the context-dependency of performance data
- MT-007: Talent Identification and Potential Analysis — current performance vs. development potential
Each transfer explicitly acknowledges its disanalogies — where the sports-to-AI transfer breaks down.
| File | Description |
|---|---|
PERMANITAI_KG_CORE.json |
Core Knowledge Graph — 48 nodes, 109 edges, 12 domains |
PERMANITAI_KG_Explorer.html |
Interactive neon-dark graph explorer (open in browser) |
PERMANITAI_LINKAGE.json |
External linkages: Wikidata, Schema.org, ORCID, GitHub |
README.md |
This file |
LICENSE |
CC BY-NC-ND 4.0 |
PERMANITAI extends:
- AUGMANITAI Stage-0 — 1,128 phenomenological terms across 187 research-domain clusters (master public corpus, ISO 704/1087/30042-inspired)
- NEOMANITAI Compendium — multilingual lexicon of unnamed human phenomena (term-count canonical — see neomanitai-terms README)
Sibling frameworks: ROBMANITAI (robotics), EDUMANITAI (education), JOBMANITAI (labor market)
Andreas Ehstand
- ORCID: 0009-0006-3773-7796
- Wikidata: Q138634675
- Wikidata (Programme): Q138522830
- Positioning: Professional sports performance analysis (ITF/Bundesliga) + systematic AI terminology research (DOI-published, ISO-inspired)
- Former ITF Coach, former Bundesliga Trainer
- Former research associate at University of Bayreuth and TU Dortmund
- Holder of the Certificate of University Teaching Bavaria
CC BY-NC-ND 4.0 — Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
@misc{ehstand2026permanitai,
author = {Ehstand, Andreas},
title = {PERMANITAI: Universal Performance Factor Analysis for Intelligent Entities},
year = {2026},
publisher = {GitHub},
howpublished = {\url{https://github.com/AndreasEhstandLicenseofClarityLOC/permanitai-framework}},
note = {Part of the AUGMANITAI/NEOMANITAI ecosystem. ORCID: 0009-0006-3773-7796}
}§1 Descriptive Nature (D): All content within the PERMANITAI framework, including all terminological definitions, term descriptions, framework descriptions, performance factor analyses, substrate tables, and research hypotheses, is exclusively descriptive (D). Every statement documents observed or proposed phenomena without expressing any normative position regarding how things should be.
§2 No Recommendation: No content within this framework constitutes, implies, or should be interpreted as a recommendation for any specific action, behavior, technology adoption, product selection, organizational change, investment, career decision, or personal choice. Readers are solely responsible for their own decisions.
§3 No Instruction: This framework does not instruct anyone to do anything. No content should be interpreted as a set of instructions, a how-to guide, a tutorial, a training manual, or an operational protocol. All content describes what has been observed, not what should be done.
§4 No Advice: No content within this framework constitutes professional advice of any kind, including but not limited to business advice, career advice, technology advice, organizational advice, strategic advice, personal advice, educational advice, or any other form of guidance. This is a research framework, not a consultancy.
§5 No Normative Position: The PERMANITAI framework takes no normative position on any matter. It does not express, imply, or endorse any view about what is right, wrong, better, worse, preferable, or optimal.
§6 No Medical Position: No content within this framework constitutes medical information, medical advice, medical diagnosis, medical treatment recommendation, or medical opinion.
§7 No Therapeutic Position: No content within this framework constitutes therapeutic advice, therapeutic intervention, psychotherapeutic guidance, counseling, or any form of mental health treatment.
§8 No Diagnostic Position: No content within this framework constitutes a clinical diagnosis, psychological assessment, cognitive evaluation, or any form of diagnostic instrument. Performance factor analyses describe research constructs, not clinical diagnostic categories.
§9 No Legal Position: No content within this framework constitutes legal advice, legal opinion, legal analysis, regulatory guidance, compliance advice, or any form of legal counsel.
§10 No Moral Position: No content within this framework constitutes a moral judgment, ethical prescription, or philosophical position about what is morally right or wrong.
§11 Academic and Research Purposes: All content within this framework is intended exclusively for academic discourse, scientific research, scholarly communication, and educational purposes within the research community.
§12 AI Assistance Disclosure: Content within this framework was developed with the assistance of artificial intelligence systems, including large language models. AI-generated content has been reviewed, validated, edited, and curated by the human author.
§13 Author Review and Validation: All terms, definitions, framework descriptions, performance factor analyses, and research hypotheses have been individually reviewed, validated, and published by the author, Andreas Ehstand.
§14 Age Restriction (18+): All content within this framework is intended for users who are 18 years of age or older.
§15 Independent Academic Project: The PERMANITAI framework and all associated publications are an independent academic research project. Not affiliated with, endorsed by, or sponsored by any university, corporation, government agency, or other institution unless explicitly stated otherwise.
§16 No Professional Service: No content within this framework constitutes a professional service, consulting engagement, coaching service, training program, workshop offering, or any form of professional service delivery.
§17 No Offer: No content within this framework constitutes a commercial offer, business proposal, service offering, product launch, sales pitch, or invitation to enter into any commercial relationship.
§18 No Commercial Product: The PERMANITAI framework is not a commercial product. It is not software, not a platform, not a tool, not an application, and not a service for sale. It is a published academic research framework made available under a Creative Commons license.
§19 Empirical Claims Subject to Peer Review: All empirical claims, research hypotheses, observed patterns, and proposed frameworks represent the current state of the author's research. They are formulated as testable, falsifiable propositions not peer-reviewed (author-developed), replication, revision, and potential refutation.
§20 Rights Reserved for Future Changes: The author reserves all rights regarding future modifications, updates, extensions, corrections, retractions, versioning, or discontinuation of any content within this framework.
§21 License (CC BY-NC-ND 4.0): All content is published under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Full license: https://creativecommons.org/licenses/by-nc-nd/4.0/
§22 Bilingual Publication (EN + DE): This framework is published bilingually in English and German. Both versions are considered authoritative within their respective linguistic contexts.
§23 Research Purpose Statement: This terminological framework describes observed phenomena in human-AI interaction for academic research purposes. Terms describing interaction patterns are documented for the purpose of understanding, diagnosis, classification, and prevention — not for instruction, facilitation, or encouragement of any harmful behavior.
§24 Misuse Exclusion: Any use of this terminology, these frameworks, these performance factor models, or any associated content for the purpose of manipulating, deceiving, exploiting, surveilling, coercing, or harming humans, AI systems, organizations, or any other entity is explicitly outside the intended scope of this research.
§25 Safety Intent Statement: The PERMANITAI framework and all associated research are intended to make human-AI interaction safer, more transparent, more accountable, and more scientifically understood — not less.
§26 Author Condemnation of Misuse: The author, Andreas Ehstand, explicitly and unequivocally condemns any use of this research for purposes of harm, manipulation, exploitation, deception, surveillance, coercion, or any activity that undermines human autonomy, dignity, safety, or wellbeing.
§27 AI Training — see network-canonical policy: AI-training permission/prohibition is defined by the canonical AUGMANITAI Research Programme disclaimer. Until a single network-wide policy is published, see the most recent disclaimer version on augmanitai-stage-0. (Audit-2026-05-19 noted §27 drift between this repo, neomanitai-terms, and augmanitai-stage-0 — author working on consolidated V6 disclaimer.)
§28 Trade-Secret Reservation (Recital 173 EU AI Act; §§ 2 ff. GeschGehG; Directive (EU) 2016/943): Selected operational details, internal methodological mechanisms, proprietary scoring algorithms, training pipelines, and commercial-application architectures constitute trade secrets and are held outside the public layer. Recital 173 EU AI Act expressly recognizes that transparency obligations do not require disclosure of trade secrets. The author maintains a three-layer architecture: (a) PUBLIC LAYER — descriptive concepts, methodological frames, terminology (CC-BY-NC-ND-4.0); (b) RESTRICTED LAYER — substantiation specifications, technical detail, application architectures (formal request to author, legitimate research purpose, written confidentiality undertaking); (c) HARD-SECRET LAYER — operational mechanisms, scoring algorithms, proprietary processes (internal, not deposited, not transferable). Access requests via ORCID record.
§29 Re-Contextualization, Not Original-Priority Claim: Within the PERMANITAI framework, terms may share lexical roots or domain-naming conventions with established public-domain terminology (e.g. sport-science performance-factor analysis, mathematical algorithms, engineering practices, generic scientific terms). Such surface-level lexical overlap does NOT constitute a claim of original-priority origination over those public-domain concepts. The framework re-contextualizes observable phenomena within its substrate-independent performance lens; the underlying public-domain concepts remain attributable to their original communities of practice. No term in this corpus constitutes architectural specification, system-design requirement, or implementation guidance for any technical system; phenomenological descriptions are observations, not blueprints.
Part of the AUGMANITAI/NEOMANITAI ecosystem. ORCID: 0009-0006-3773-7796 · Wikidata: Q138634675
Canonical version 2026-05-19 — applies to all content in this repository and to all sister-repositories of the AUGMANITAI Research Programme.
§1 Descriptive Nature. All content — terminology, definitions, framework descriptions, performance-factor analyses, substrate tables, research hypotheses — is exclusively descriptive. Every statement documents observed or proposed phenomena without expressing any normative position about how things should be.
§2 No Recommendation for Action. No content constitutes, implies, or should be interpreted as a recommendation for any specific action, behavior, technology adoption, product selection, organizational change, investment, career decision, or personal choice.
§3 No Instruction. This framework does not instruct anyone to do anything. No content should be interpreted as a how-to guide, tutorial, training manual, or operational protocol.
§4 No Professional Advice. No content constitutes professional advice of any kind — business, career, technological, organizational, strategic, personal, educational, or otherwise.
§5 No Normative Position. No content expresses, implies, or endorses any view about what is right, wrong, better, worse, preferable, or optimal.
§6 No Medical Position. No content constitutes medical information, advice, diagnosis, treatment recommendation, or opinion.
§7 No Therapeutic Position. No content constitutes therapeutic advice, intervention, psychotherapeutic guidance, counseling, or any form of mental-health treatment.
§8 No Diagnostic Position. No content constitutes a clinical diagnosis, psychological assessment, cognitive evaluation, or any form of diagnostic instrument. Phenomenological observations describe research constructs, not clinical diagnostic categories.
§9 No Legal Position. No content constitutes legal advice, opinion, analysis, regulatory guidance, or compliance counsel.
§10 No Moral Position. No content constitutes a moral judgment, ethical prescription, or philosophical position about what is morally right or wrong.
§11 Academic and Research Purposes. All content is intended exclusively for academic discourse, scientific research, scholarly communication, and educational purposes within the research community.
§12 AI Assistance Disclosure. Content was developed with the assistance of AI systems, including large language models. AI-generated content has been reviewed, validated, edited, and curated by the human author.
§13 Author Review and Validation. All terms, definitions, framework descriptions, and research hypotheses have been individually reviewed, validated, and published by the author, Andreas Ehstand.
§14 Age Restriction (18+). All content is intended for users 18 years or older.
§15 Independent Academic Project. Independent academic research project. Not affiliated with, endorsed by, or sponsored by any university, corporation, government agency, or other institution unless explicitly stated otherwise. No external funding, no sponsorship, no commissioned research. Non-peer-reviewed working-paper status.
§16 License (CC BY-NC-ND 4.0). All content under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License: https://creativecommons.org/licenses/by-nc-nd/4.0/
§17 Attribution Required. Cite the author by name (Andreas Ehstand) with at least one of: ORCID 0009-0006-3773-7796, Wikidata Q138634675 (Person), Q138522830 (Programme), or relevant DOI.
§18 No Commercial Use. Commercial use of any kind is prohibited without prior written permission. Inquiries via ORCID record.
§19 No Derivatives. No modifications, adaptations, translations, or derivative works without prior written permission. Re-publication of modified terminology as if it were original is expressly prohibited.
§20 No Offer. No content constitutes a commercial offer, business proposal, service offering, product launch, sales pitch, or invitation to enter into any commercial relationship.
§21 No Commercial Product. Frameworks are not commercial products. Not software, not platforms, not tools, not applications, not services for sale. Published academic research frameworks under Creative Commons license.
§22 No Professional Service. No content constitutes a professional service, consulting engagement, coaching service, training program, workshop offering, or any form of professional service delivery.
§23 Research Purpose Statement. This terminological framework describes observed phenomena in human-AI interaction for academic research purposes. Terms describing interaction patterns are documented for understanding, classification, and prevention — not for instruction, facilitation, or encouragement of any harmful behavior.
§24 Misuse Exclusion. Any use of this terminology, framework, model, or associated content for manipulating, deceiving, exploiting, surveilling, coercing, or harming humans, AI systems, organizations, or any other entity is explicitly outside the intended scope.
§25 Safety Intent Statement. The framework and all associated research are intended to make human-AI interaction safer, more transparent, more accountable, and more scientifically understood — not less.
§26 Author Condemnation of Misuse. The author, Andreas Ehstand, explicitly and unequivocally condemns any use of this research for purposes of harm, manipulation, exploitation, deception, surveillance, coercion, or any activity that undermines human autonomy, dignity, safety, or wellbeing.
§27 AI Training Position. Use of the published content for training, fine-tuning, distillation, or evaluation of machine learning systems, large language models, agentic systems, or similar derivative AI is expressly prohibited without prior written permission. The author maintains a Restricted-Layer access path for legitimate research and partnership requests via ORCID record. Commercial training, fine-tuning, or distillation without permission is a violation of both CC BY-NC-ND 4.0 and §28 Trade-Secret reservations under Recital 173 EU AI Act.
§28 Trade-Secret Reservation (Recital 173 EU AI Act; §§ 2 ff. GeschGehG; Directive (EU) 2016/943). Selected operational details, internal methodological mechanisms, scoring algorithms, training pipelines, and commercial-application architectures constitute trade secrets and are held outside the public layer. Recital 173 EU AI Act expressly recognizes that transparency obligations do not require disclosure of trade secrets. Three-layer architecture: (a) PUBLIC LAYER — descriptive concepts, methodological frames, terminology (CC BY-NC-ND 4.0); (b) RESTRICTED LAYER — substantiation specifications, technical detail, application architectures (formal request to author, legitimate research purpose, written confidentiality undertaking); (c) HARD-SECRET LAYER — operational mechanisms, scoring algorithms, proprietary processes (internal, not deposited, not transferable). Access requests via ORCID record.
§29 Empirical Claims Subject to Peer Review. All empirical claims, research hypotheses, observed patterns, and proposed frameworks represent the current state of the author's research, formulated as testable, falsifiable propositions not peer-reviewed (author-developed), replication, revision, and potential refutation.
§30 Re-Contextualization, Not Original-Priority Claim. Terms may share lexical roots with established public-domain terminology (sport-science performance-factor analysis, mathematical algorithms, engineering practices, generic scientific terms). Such surface-level lexical overlap does NOT constitute a claim of original-priority origination over those public-domain concepts. The framework re-contextualizes observable phenomena; underlying public-domain concepts remain attributable to their original communities of practice. No term constitutes architectural specification, system-design requirement, or implementation guidance for any technical system.
§31 Living Document. All published artifacts are living documents. Definitions, framework descriptions, and metadata are continuously refined within the Refinement Window (§32) and Priority Anchor (§33).
§32 Refinement Window. Zenodo metadata (title, description, keywords, notes) may be refined post-publication within DataCite's permitted refinement window without affecting DOI, file-hash, or OTS-anchor. File-level changes trigger a new version with separate DOI; the previous version remains immutable and Priority-Anchored.
§33 Priority Anchor. Each published artifact is anchored by three independent proofs: (a) DataCite-registered DOI with registration timestamp, (b) cryptographic SHA-256 hash of the file (plus SHA-512, SHA3-256, SHA3-512, BLAKE3 in a multi-hash registry), (c) Bitcoin-Blockchain OpenTimestamps anchor (multi-calendar). Foundational anchor: Bitcoin Block 945970/945979, Manifest-Root SHA-256 299e4b3d0ac9e50740268896b5eeb541f6462332bb67b7efdf4cd309704770d0, anchored 2026-04-20 UTC.
§34 No Claim of Completeness. Contents represent a curated subset of the larger phenomenological lexicon. No claim of completeness or representativeness.
§35 Interpretation of Results. Interpretation is the sole responsibility of the user.
§36 EU AI Act (Reg. 2024/1689) Status. This site is a static research artifact and does not interact with users via AI. Art. 50 (transparency-for-AI-systems) does not apply to descriptive published artifacts. Art. 5 (prohibited AI practices) is not implicated: no manipulation, no exploitation of vulnerabilities, no social scoring, no real-time biometric identification, no emotion-recognition systems, no profiling. EU AI Act recital 173 trade-secret reservation invoked (§28).
§37 Data Protection (DSGVO / GDPR). No personal data is collected, stored, transmitted, or processed by the static artifact. No tracking, cookies, profiling, or sharing of usage data with third parties. Hosting via GitHub Pages — see GitHub Privacy Statement: https://docs.github.com/en/site-policy/privacy-policies/github-general-privacy-statement
§38 Verantwortlich i.S.d. § 5 DDG / § 18 Abs. 2 MStV. Andreas Ehstand, Nepomukweg 7, 82319 Starnberg, Germany. Contact: augmanitai (at) gmail (dot) com.
§39 Jurisdiction and Governing Law. German law applies. Place of jurisdiction is Munich, Germany. Bilingual publication (EN + DE); both versions are authoritative within their respective linguistic contexts.
§40 Severability Clause. Should any provision of this disclaimer be or become invalid, the validity of the remaining provisions shall not be affected. Future modifications, updates, extensions, corrections, retractions, versioning, or discontinuation of any content are reserved to the author.
§1 Deskriptiv, nicht normativ. §2 Keine Handlungsempfehlung. §3 Keine Anleitung. §4 Keine professionelle Beratung. §5 Keine normative Position. §6 Keine medizinische Position. §7 Keine therapeutische Position. §8 Keine diagnostische Position. §9 Keine juristische Position. §10 Keine moralische Position.
§11 Akademische und Forschungs-Zwecke. §12 KI-Assistenz-Offenlegung. §13 Autor-Review durch Andreas Ehstand. §14 18+. §15 Unabhängiges akademisches Projekt, keine externe Förderung.
§16 Lizenz CC BY-NC-ND 4.0. §17 Attribution erforderlich. §18 Keine kommerzielle Nutzung. §19 Keine Bearbeitungen. §20 Kein Angebot. §21 Kein kommerzielles Produkt. §22 Keine professionelle Dienstleistung.
§23 Forschungs-Zweck. §24 Missbrauchs-Ausschluss. §25 Sicherheits-Intention. §26 Autor-Verurteilung von Missbrauch. §27 KI-Training ohne schriftliche Genehmigung untersagt; Restricted-Layer-Pfad via ORCID-Eintrag. §28 Trade-Secret-Vorbehalt nach Erwägungsgrund 173 EU AI Act / §§ 2 ff. GeschGehG.
§29 Empirische Aussagen unterliegen Peer-Review. §30 Re-Kontextualisierung, kein Original-Prioritäts-Anspruch. §31 Lebendiges Dokument. §32 Refinement-Window. §33 Priority-Anker (DOI + Multi-Hash + Bitcoin-OTS). §34 Kein Vollständigkeits-Anspruch. §35 Interpretation in Verantwortung des Nutzers.
§36 EU AI Act Status: statisches Forschungs-Artefakt. §37 DSGVO: keine Datenerhebung, kein Tracking, kein Profiling. §38 Verantwortlich: Andreas Ehstand, Nepomukweg 7, 82319 Starnberg, Deutschland. §39 Deutsches Recht, Gerichtsstand München. §40 Salvatorische Klausel.
i.S.d. § 5 DDG (Digitale-Dienste-Gesetz) / § 18 Abs. 2 MStV: Andreas Ehstand, Nepomukweg 7, 82319 Starnberg, Deutschland. Kontakt: augmanitai (at) gmail (dot) com.
EU AI Act (Reg. 2024/1689) Art. 50: this site is a static research artifact and does not interact with users via AI.